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The growing integration of renewable energy sources (RES) into the power system causes congestion to occur more frequently. In order to reduce congestion in the short term and to make the utilization of the power system more efficient in the long term, power flow control (PFC) in the transmission system has been proposed. However, exemplary studies show that congestion will increase also in the distribution system if the transmission system is expanded. For this reason, the potential of PFC to reduce congestion in a model of a real 110 kV distribution system is investigated. Several Unified Power Flow Controller (UPFC) devices are optimized in terms of their number and placement in the power system, their size, control parameters, and costs, by using a Parallel Tempering approach as well as a greedy algorithm. Two optimization variants are considered, one reducing the number of degrees of freedom by integrating system knowledge while the other does not. It is found that near a critical grid state and disregarding costs, PFC can reduce congestion significantly (99.13%). When costs of the UPFCs are taken into account, PFC can reduce congestion by 73.2%. A basic economic analysis of the costs reveals that the usage of UPFCs is profitable. Furthermore, it is found that the reduction in the solution space of the optimization problem leads to better results faster and that, contrary to expectations, the optimization problem is simple to solve. The developed methods allow not only for the determination of the optimal use of UPFCs to minimize congestion, but also to estimate their profitability. [ABSTRACT FROM AUTHOR]

To draw reliable conclusions about the thermal characteristic of or a preferential cooling strategy for a lithium-ion battery, the correct set of thermal input parameters and a detailed battery layout is crucial. In our previous work, an electrochemical model for a commercially-available, 40 Ah prismatic lithium-ion battery was validated under heuristic temperature dependence. In this work the validated electrochemical model is coupled to a spatially resolved, three dimensional (3D), thermal model of the same battery to evaluate the thermal characteristics, i.e., thermal barriers and preferential heat rejection patterns, within common environment layouts. We discuss to which extent the knowledge of the batteries' interior layout can be constructively used for the design of an exterior battery thermal management. It is found from the study results that: (1) Increasing the current rate without considering an increased heat removal flux at natural convection at higher temperatures will lead to increased model deviations; (2) Centralized fan air-cooling within a climate chamber in a multi cell test arrangement can lead to significantly different thermal characteristics at each battery cell; (3) Increasing the interfacial surface area, at which preferential battery interior and exterior heat rejection match, can significantly lower the temperature rise and inhomogeneity within the electrode stack and increase the batteries' lifespan. [ABSTRACT FROM AUTHOR]

The key challenge in developing a physico-chemical model is the model parameterization. The paper presents a strategic model parameterization procedure, parameter values, and a developed model that allows simulating electrochemical and thermal behavior of a commercial lithium-ion battery with high accuracy. Steps taken are the analysis of geometry details by opening a battery cell under argon atmosphere, building upon reference data of similar material compositions, incorporating cell balancing by a quasi-open-circuit-voltage experiment, and adapting the battery models reaction kinetics behavior by comparing experiment and simulation of an electrochemical impedance spectroscopy and hybrid pulse power characterization. The electrochemical-thermal coupled model is established based on COMSOL Multiphysics® platform (Stockholm, Sweden) and validated via experimental methods. The parameterized model was adopted to analyze the heat dissipation sources based on the internal states of the battery at different operation modes. Simulation in the field of thermal management for lithium-ion batteries highly depends on state of charge-related thermal issues of the incorporated cell composition. The electrode balancing is an essential step to be performed in order to address the internal battery states realistically. The individual contribution of the cell components heat dissipation has significant influence on the temperature distribution pattern based on the kinetic and thermodynamic properties. [ABSTRACT FROM AUTHOR]

Mr. O. Zahid was not included in the acknowledgement section with respect to illustrations created from geometric and thermal battery cell data he generated during his master's thesis study independent of the original publication. The corrected acknowledgement appears here: The authors thank O. Zahid for the geometric characterization of the commercial battery cell and the derived thermal parameters, the properties of which were further investigated in this study by numerical analysis. Reference 1 Liebig G., Gupta G., Kirstein U., Schuldt F., Agert C. Parameterization and Validation of an Electrochemical Thermal Model of a Lithium-Ion Battery. [Extracted from the article]

Footnotes 1 B Disclaimer/Publisher's Note: b The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). Mr. Omio Zahid was not included as an author in the original publication [[1]]. The reason behind the requirement for the correction of the publication is the ex-post appreciation of the scientific contributions of Mr. Zahid according to the rules of good scientific practice at the University of Oldenburg [[1]]. [Extracted from the article]

Hydrogen is becoming an increasingly important energy carrier in sector integration for fuel cell transportation, heat and electricity. Underground salt caverns are one of the most promising ways to store the hydrogen obtained from water electrolysis using power generation from renewable energy sources (RES). At the same time, the production of hydrogen can be used to avoid energy curtailments during times of low electricity demand or low prices. The stored hydrogen can also be used during times of high energy demand for power generation, e.g., with fuel cells, to cover the fluctuations and shortages caused by low RES generation. This article presents an overview of the techniques that were used and proposed for using excess energy from RES for hydrogen production from water and its storage techniques, especially in underground salt caverns, for the aforementioned purpose, and its feasibility. This paper compares and summarizes the competing technologies based on the current state-of-the-art, identifies some of the difficulties in hydrogen production and storage, and discusses which technology is the most promising. The related analysis compares cost and techno-economic feasibility with regard to hydrogen production and storage systems. The paper also identifies the potential, technical challenges and the limitations associated with hydrogen integration into the power grid. [ABSTRACT FROM AUTHOR]

As a consequence of the increasing share of renewable energies and sector coupling technologies, new approaches are needed for the study, planning, and control of modern energy systems. Such new structures may add extra stress to the electric grid, as is the case with heat pumps and electrical vehicles. Therefore, the optimal performance of the system must be estimated considering the constraints imposed by the different sectors. In this research, an energy system dispatch optimization model is employed. It includes an iterative approach for generating grid constraints, which is decoupled from the linear unit commitment problem. The dispatch of all energy carriers in the system is optimized while considering the physical electrical grid limits. From the considered scenarios, it was found that in a typical German neighborhood with 150 households, a PV penetration of ∼5 kWp per household can lead to curtailment of ∼60 MWh per year due to line loading. Furthermore, the proposed method eliminates grid violations due to the addition of new sectors and reduces the energy curtailment up to 45 % . With the optimization of the heat pump operation, an increase of 7 % of the self-consumption was achieved with similar results for the combination of battery systems and electrical vehicles. In conclusion, a safe and optimal operation of a complex energy system is fulfilled. Efficient control strategies and more accurate plant sizing could be derived from this work. [ABSTRACT FROM AUTHOR]

Power system security is increasingly endangered due to novel power flow situations caused by the growing integration of distributed generation. Consequently, grid operators are forced to request the curtailment of distributed generators to ensure the compliance with operational limits more often. This research proposes a framework to simulate the incidental amount of renewable energy curtailment based on load flow analysis of the network. Real data from a 110 kV distribution network located in Germany are used to validate the proposed framework by implementing best practice curtailment approaches. Furthermore, novel operational concepts are investigated to improve the practical implementation of distributed generation curtailment. Specifically, smaller curtailment level increments, coordinated selection methods, and an extension of the n-1 security criterion are analyzed. Moreover, combinations of these concepts are considered to depict interdependencies between several operational aspects. The results quantify the potential of the proposed concepts to improve established grid operation practices by minimizing distributed generation curtailment and, thus, maximizing power system integration of renewable energies. In particular, the extension of the n-1 criterion offers significant potential to reduce curtailment by up to 94.8% through a more efficient utilization of grid capacities. [ABSTRACT FROM AUTHOR]

An energy management system (EMS) for a household energy system is proposed in this paper, which is composed of a photovoltaic (PV) generator, a home energy storage (HES), an electric vehicle (EV), an electrical household load and a grid connection, with 24 h operation horizon. The EMS objective is to reduce the electricity cost of the household by using a linear optimization algorithm. Two different EV schedules are utilized for simulations. One mainly describes rides to work and the other describes rides in a domestic context, such as rides to a supermarket. A forecast algorithm for the electrical load of the household, based on k-means clustering and an artificial neural network, is evaluated and integrated into the EMS to realistically represent the household's load profile. It is shown that the developed forecast algorithm performs better than two of the benchmarks. Another finding is that the more storage is available at PV-production intervals, the higher the effect of forecast uncertainties and the lower the electricity cost of the household, disregarding the investment cost. [ABSTRACT FROM AUTHOR]